SOURCE-LINKED INTELLIGENCE
MoSAT: Human Motion Generation from Spatial Audio and Textual Description
Human motion is shaped by both external acoustic events and behavioral intent: spatial audio conveys environmental cues that elicit or guide a response, while text specifies the desired action and how it should be performed. In this paper, we study the novel task of human motion synthesis jointly conditioned on spatial audio and natural language, a problem that has been largely overlooked in previous research. To support this task, We introduce STAM, a dataset of motion sequences paired with spatial audio and detailed textual annotations whose rich vocabulary affords precise and nuanced specif
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-20T18:38:41.000Z
First collected: 2026-09-23T09:51:33.063Z. This is not the publication date.